Accelerating AI innovation through adaptive, right-sized governance
AI is moving fast—and for many federal agencies, governance is struggling to keep up. That uncertainty slows innovation and makes it harder for organizations to move forward with confidence. But the solution isn’t to pump the brakes—it’s to put the right guardrails in place. The federal government agrees, as we’ve seen in OMB Memos M-25-21 and M-25-22.
Scaling artificial intelligence (AI) successfully demands governance that does more than check boxes. It must be adaptive, practical, and evolve alongside the technology itself. When done well, AI governance isn’t just about compliance—it’s a catalyst. It accelerates smart deployment, builds stakeholder trust, and ensures that innovation happens responsibly.
“Effective AI governance is key to accelerated innovation as it empowers professionals at all levels to align processes, establish clear policies, and foster accountability while reducing unnecessary barriers to AI adoption.”
At ICF, we believe the future of AI belongs to those who can govern it wisely. That means creating frameworks that are right-sized to the risk, built on proven business practices, and flexible enough to meet emerging needs—without slowing down the pace of progress.
Let’s explore how.
Scaling and deploying AI at speed requires governance that protects and provides confidence. While the technology and its usage introduce new and unknown challenges, overly rigid policies can stifle experimentation and limit AI’s impact.
We can all agree that AI brings both promise and uncertainty. But its full potential requires governance models that are adaptive, proportional, and responsive to change—time-tested business practices like risk assessments, compliance audits, and incident response plans make use of these principles. Using them as a foundation ensures that AI supports your organization’s mission, meets performance goals, and aligns with stakeholder expectations.
When governance is designed to grow with your technology and your organization, it becomes more than a safeguard—it becomes a strategic advantage.
Key principles for AI governance that fuels innovation and drives trust:
- AI risks aren’t equal, so stop treating them that way: AI governance should be tiered. A chatbot generating FAQs and an AI system approving federal grants do not require the same level of oversight. Organizations should apply risk registers to map the likelihood versus severity and govern accordingly.
- Build from what already works: AI governance does not need to start from scratch. Instead of re-inventing the wheel, adapt frameworks like the National Institute for Standards and Technology’s AI Risk Management Framework () as the starting point. [Editor’s Note: See how we apply this framework to build responsible AI solutions for government clients.] Organizations can easily do this by:
- Performing a gap analysis to assess unmet needs, bright spots, and inefficiencies
- the identified framework to address the most relevant risks
- Integrating governance actions and priorities into existing organizational processes
- Building awareness, through training and communications, to ensure employees can adopt the desired behaviors and actions
- Transparency that benefits teams as much as the organization: Explainability shouldn’t be a compliance checkbox, it should be a tool for continuous learning and improvement. Per OMB Memo M-25-22, page 6, section 3.e.v., model documentation and decision logs should be in place to help teams refine AI as well as satisfy regulators.
- Use governance to go faster: As OMB Memo M-25-21 states, “Effective AI governance is key to accelerated innovation.” The best governance models act as growth levers, streamlining approvals and reducing internal friction, allowing organizations to deploy AI faster while maintaining security, fairness, and accountability.
The goal should be “smart-scale” or “right-sized” governance that is targeted, efficient, and risk-adjusted, with no wasted effort or overreach.
Move fast and fix things: Next steps for your organization
- Assess your governance practices to identify inefficiencies, gaps, and risks.
- Develop an adaptive, right-sized AI governance framework that complies with the most current OMB guidance, and tailor an existing framework, like NIST AI RMF, to your organization’s needs. Keep your framework flexible and adaptable by engaging stakeholders, encouraging robust feedback and discussion, and establishing performance assessments or audits. For example, an OMB-mandated governance board brings all these elements together, coordinating and governing issues related to the use of AI within the Executive Branch.
- Consider establishing an AI Governance Board or team to help your organization continuously monitor and quickly adapt as AI capabilities evolve. For federal agencies, this board will be made up of stakeholders and led by a Chief AI Officer (CAIO) and will be tasked with coordinating and governing issues related to the use of AI. A similar team in your organization can keep their fingers on the pulse of internal and external needs and ensure that they’re being met.
AI governance should protect and help organizations approach innovation with responsibility and purpose. The right approach ensures organizations achieve the benefits of AI quickly while scaling confidently—enabling agencies to focus on what truly matters.
At ICF, we help public and private sector organizations implement right-sized governance that protects stakeholders, inspires trust, and accelerates the deployment of AI solutions. Our approach blends long-standing business practices like risk assessments, compliance audits, and incident response planning with clear, forward-looking principles tailored to the dynamic nature of AI. We also have the experience and expertise to guide you through evolving government AI guidelines. By aligning oversight with strategy and regulation with innovation, we help you make smarter decisions, faster.